MCP Google Maps

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. For example, get_directions is for routing, get_distance_matrix is for multi-point calculations, and get_geocode vs get_reverse_geocode handle opposite conversions. The descriptions reinforce these unique functions, making tool selection straightforward.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with 'get_' or 'search_' prefixes, such as get_directions, get_geocode, and search_nearby. This uniformity enhances readability and predictability, allowing agents to easily understand the tool set's structure.
Tool Count5/5
With 8 tools, the count is well-scoped for a Google Maps server, covering core functionalities like directions, geocoding, place search, and maps. Each tool earns its place by addressing a specific aspect of location-based services without redundancy or bloat.
Completeness5/5
The tool set provides complete coverage for the Google Maps domain, including routing (directions, distance matrix), geospatial conversions (geocode, reverse geocode), place information (details, nearby search), and visualization (map with directions). No obvious gaps exist, enabling agents to handle typical mapping workflows effectively.
Average 3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'static map' (implying a read-only image output) and 'directions overlay' (suggesting visual routing), but lacks critical details: what format the output takes (image URL? binary data?), whether there are rate limits, authentication requirements, cost implications, or error conditions. For a tool with 7 parameters and complex functionality, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is maximally concise - a single 6-word sentence that front-loads the core functionality. Every word earns its place: 'Generate' (action), 'static map' (primary output), 'with directions overlay' (key feature). There's zero redundancy or wasted verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, nested objects, no output schema, no annotations), the description is severely incomplete. It doesn't address output format, error handling, usage constraints, or parameter semantics. While conciseness is good, this tool requires more context for effective use - especially with siblings that handle related geospatial functions where confusion is likely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% - none of the 7 parameters have descriptions in the schema. The tool description adds minimal value: it implies 'origin' and 'destination' parameters through 'directions overlay' context, and suggests map customization through 'static map,' but doesn't explain any of the specific parameters (waypoints, mode, size, scale, mapType) or their relationships. With 7 undocumented parameters, the description fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a static map with directions overlay' - this specifies the action (generate), resource (static map), and key feature (directions overlay). It distinguishes from siblings like 'get_directions' (which likely returns directions data rather than a map) and 'get_distance_matrix' (which calculates distances). However, it doesn't explicitly contrast with these alternatives, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the 6 sibling tools. There's no mention of alternatives, prerequisites, or specific use cases. The agent must infer from tool names alone, which is insufficient for clear decision-making between similar mapping/direction tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'get directions' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns structured vs. textual directions, includes estimated times/costs, or handles errors. For a tool with 3 parameters and no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a straightforward tool and gets directly to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a directions tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what format the directions are returned in (textual, structured, with waypoints), whether it includes real-time traffic, or what the typical response looks like. The agent would have to invoke the tool blindly to understand its behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all parameters well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema (origin, destination, mode with enum values). This meets the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and resource 'directions' with the scope 'between two locations', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_distance_matrix' or 'get_map_with_directions' which might provide similar or overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_distance_matrix' (which might provide distance/time without full directions) or 'get_map_with_directions' (which might include visual output). There's no mention of prerequisites, limitations, or appropriate contexts for choosing this specific tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states what the tool does but reveals nothing about rate limits, authentication requirements, data sources, accuracy, units of measurement, or error handling. For a geospatial tool with no annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a straightforward data retrieval tool and gets directly to the point with zero wasted verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a geospatial data tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the elevation data returns in, what units are used, whether there are limitations on location count, or how to interpret results. The agent would need to guess about important operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'locations' well-documented in the schema as an array of latitude/longitude objects. The description adds no additional parameter semantics beyond what's already in the structured schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('elevation data for locations'), making the purpose immediately understandable. It distinguishes itself from siblings like get_directions or get_geocode by focusing specifically on elevation. However, it doesn't specify whether this is for single or multiple locations, which could be more precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like get_geocode and get_reverse_geocode that handle location data differently, there's no indication of when elevation data is needed or what specific use cases this tool addresses. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Convert' implies a read-only operation, it doesn't address rate limits, accuracy expectations, error handling, or what format the coordinates will be returned in. This leaves significant gaps for an AI agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise at just four words, front-loading the core functionality without any wasted language. Every word earns its place in communicating the essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a geocoding tool with no annotations and no output schema, the description is insufficient. It doesn't explain what coordinate system is used, whether it returns latitude/longitude pairs, accuracy metrics, or how to interpret results. The agent would need to guess about the tool's output format and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, with the single parameter 'address' clearly documented. The description doesn't add any meaningful semantic context beyond what the schema already provides, such as examples of valid address formats or handling of ambiguous inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Convert') and resource ('address to coordinates'), making it immediately understandable. However, it doesn't explicitly distinguish this tool from its sibling 'get_reverse_geocode', which presumably does the opposite conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_place_details' and 'search_nearby' available, there's no indication of when address-to-coordinate conversion is preferred over other geospatial operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the basic action but doesn't cover critical aspects like rate limits, authentication requirements, pagination, error handling, or what the output looks like (e.g., list format, fields included). This leaves significant gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, nested objects, no output schema) and lack of annotations, the description is insufficient. It doesn't explain return values, error cases, or behavioral nuances, leaving the agent with incomplete context for proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 80%, so the schema already documents most parameters well. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify 'center' usage or 'keyword' examples beyond the schema's descriptions). This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Search for places near a specific location,' which includes a specific verb ('Search') and resource ('places near a specific location'). However, it doesn't explicitly differentiate from sibling tools like 'get_place_details' or 'get_geocode,' which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context such as whether this is for general discovery versus specific lookups, and doesn't mention sibling tools like 'get_place_details' for detailed information or 'get_geocode' for location resolution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool calculates distance and time, but doesn't mention performance characteristics (e.g., rate limits, latency), error handling, or output format details. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is minimally adequate for a calculation tool but lacks completeness. It doesn't explain what the output looks like (e.g., matrix format, units), error conditions, or limitations (e.g., maximum origins/destinations). For a tool with 3 parameters and no structured output documentation, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain format requirements for addresses/coordinates or clarify the 'mode' enum). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resources 'distance and time between multiple origins and destinations', which is specific and actionable. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_directions' or 'get_map_with_directions', which might offer similar routing functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_directions' or 'get_map_with_directions'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'gets' information, implying a read-only operation, but doesn't clarify aspects like rate limits, authentication needs, error handling, or what 'detailed information' entails (e.g., fields returned). This leaves significant gaps for a tool with no structured safety hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Get detailed information about a specific place') contributes directly to understanding the tool's function, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no nested objects) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it fails to explain behavioral traits or return values, leaving gaps in completeness. It meets the baseline for a simple tool but doesn't fully compensate for the lack of structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'placeId' documented as a 'Google Maps Place ID'. The description adds no additional meaning beyond this, such as format examples or where to obtain the ID. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but there's no extra value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get detailed information') and resource ('about a specific place'), making the purpose understandable. It distinguishes from siblings like get_directions or search_nearby by focusing on details for a single place rather than routing or searching. However, it doesn't specify what 'detailed information' includes, which slightly reduces specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a placeId), exclusions, or comparisons to siblings like get_geocode (for address lookup) or search_nearby (for finding places). Usage is implied by the name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'convert' implies a read-only transformation, the description doesn't mention any behavioral traits like rate limits, accuracy considerations, data source, error handling, or what happens with invalid coordinates. For a tool with no annotation coverage, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise - a single sentence that directly states the tool's purpose with zero wasted words. It's front-loaded with the core functionality and doesn't include any unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple coordinate-to-address conversion tool with 2 parameters and 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it should ideally provide more context about what kind of address format is returned, accuracy considerations, or limitations. The description meets basic requirements but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters. The description adds no additional parameter semantics beyond what's in the schema (latitude and longitude as coordinates). The baseline score of 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('convert') and resource ('coordinates to an address'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_geocode' (which likely converts addresses to coordinates), leaving some ambiguity about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_geocode' (likely the inverse operation) and 'search_nearby' (which might also use coordinates), there's no indication of when this specific reverse geocoding tool is preferred over other coordinate-based tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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